Identification of Antioxidant Additives in Food Products Sold in Dakar Markets

The use of food additives in industrial production has the advantage of improving sensory properties, technological quality and extending the shelf life of foods. Among the most widely used additives are antioxidants, which prevent oxidation, browning and rancidity reactions in foods. However, the strong presence of these additives on the market is not without risks for human health, and should be controlled to guarantee food safety. Analysis of the risks associated with consumption of foods containing these additives requires, among other things, information on the frequency of use of these additives in various consumer products. The aim of this study is therefore to identify the antioxidants present in industrial food products distributed in Dakar. The methodology adopted consists of a qualitative analysis based on the identification of additives from food labels. Investigations were carried out in 9 stores, 4 superettes and 2 supermarkets located in different districts of Dakar. The results revealed the presence of 12 antioxidant additives, dominated by citric acid (53%) and ascorbic acid (29%). These studies have also highlighted the simultaneous use of several antioxidants in the same food product. Moreover, for some artificial antioxidants identified antioxydant such as BHA and BHT, health risks are associated with their consumption. The results of this study open up prospects for the development of information databases on food additives.

Physicochemical Properties and Health Risks of Informal E-Waste Processing at Alaba International Market in Lagos, Nigeria

This study investigated the groundwater quality and health risks associated with informal e-waste processing in the Alaba International Market in Lagos, Nigeria. Twenty-two groundwater samples were collected from hand-dug wells in the market area and analyzed for physicochemical properties and heavy metal concentrations. The results showed that the groundwater quality was poor, with high levels of heavy metals, including cadmium, lead, and chromium. The health index (HI) for children and adults was above the tolerable threshold levels, indicating a potential health risk to the population. Principal component analysis and hierarchical cluster analysis were used to identify the sources of metals in groundwater, and the results showed that informal e-waste processing was a significant source of contamination. The study highlights the need for effective management strategies to mitigate the potential health risks associated with informal e-waste processing and ensure public health and environmental safety.

PRICING EUROPEAN OPTION IN A DOUBLE EXPONENTIAL JUMP-DIFFUSION MODEL WITH TWO MARKET STRUCTURE RISKS AND ITS COMPARISONS

Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.

Analysis of Conditional Value-at-Risk for Newsvendor with Holding and Backorder Cost under Market Search

We consider a distribution system with one supplier and two retailers. For the two retailers, they face different demand and are both risk averse. We study a single period model which the supplier has ample goods and the retailers order goods separately. Market search is measured as the fraction of customers who unsatisfied with their ＂local＂ retailer due to stock-out, and search for the goods at the other retailer before leaving the system. We investigate how the retailers game for order quantity in a Conditional Value-at-Risk framework and study how risk averse degree, market search level, holding cost and backorder cost influence the optimal order strategies. Furthermore, we use uniform distribution to illustrate these results and obtain Nash equilibrium of order strategies.

Risk identification and regulatory system design for the carbon market

Currently,the global carbon trading systems are fragmented and belong to different governments or are under the jurisdiction of different regions,resulting in a series of new problems,such as how to link dispersed trading systems,how to compare the emission reduction of various markets and other issues.Since the development of the international carbon market is relatively immature with uncertain life expectancy and volatility during its short history,and there is a lack of quantitative data on the long-term record,the market could provide few risk management tools.Meanwhile,with the launches of China's regional carbon trading pilots in seven provinces since 2013 and combined with the national voluntary emission trading system,carbon trading will become an important mechanism for China in achieving its emission reduction target.In the first stage,the carbon finance market is at least faced with mechanism design risks,market supply risks and compliance risks.Therefore,to secure the development of the carbon market and for public interest,relevant government departments of China should identify the risks facing the market and should make the basic principles and goals,such as ensuring effective trading and pricing mechanisms to avoid fraud and price manipulation,and balancing transparency and confidentiality of information.Consequently,the governments should develop a comprehensive carbon finance regulatory system covering regulatory legislation,regulatory institutions and their authorities,regulatory scope as well as regulatory objects.

Study of Enterprises Marketing Risk Early Warning System Based on BP Neural Network Model

For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and combined with the practical conditions of dairy enterprises, the index system caused by the marketing risk was also studied. The principal component method was used for screening the indexes, the grades and critical values of the marketing risk were determined. Through the configuration of BP network, node processing and error analysis, the early warning results of the marketing risk were obtained. The results indicate that BP neural network method can be effectively applied through the function approach in the marketing early warning with incomplete information and complex varied conditions.

Research on Market Risk Assessment of Dairy Farms: Taking 75 Dairy Farms in Heilongjiang Province as Examples

Based on the investigation and research on 75 dairy farms in Heilongjiang Province, evaluation index system of dairy farm market risk was set up, and dairy farm market risks were divided into pairing risk, price risk, production risk, contract risk and policy risk, five aspects of a total of 12 assessment indicators. The fuzzy comprehensive evaluation method was used to evaluate the market risk. The evaluation results showed that the market risk of dairy farms in Heilongjiang Province was at low risk; however, the policy risk was high. Finally, according to the results of the assessment, the suggestions was made as the followings： the government should expand the scope of policy insurance for dairy farming, vigorously promote the development of cooperative organizations and intermediary organizations in dairy farms by purchasing services through government, increase their functional roles and establish strict supervision mechanisms, including the establishment of official advice hotline and consultation channel online and improving third-party testing mechanism; government and the department of management industry would improve their abilities of management and do a good job of training and guiding.

Prevention of Agricultural Market Risks by Agricultural Production Entities in Hubei Province

Different agricultural production and operation entities face the same market risks.Since there is a huge gap in market risk prevention ability between agricultural market operation entities,the gap of risk prevention effect is huge.Using statistical analysis and comparative analysis methods,this paper analyzed characteristics and influencing factors of agricultural market risks and pointed out characteristics of agricultural market and special characteristics of agricultural production and operation entities in Hubei Province.Based on SWOT analysis on market risk prevention ability of agricultural production and operation entities in Hubei Province,it came up with three recommendations,including upgrading agricultural production and operation entities,enlarging the production and operation scale,and strengthening the ability of balancing the market demand and supply and bargaining power and pricing power.

A Statistical Measure of Global Equity Market Risk

We construct a new index of global equity market risk (EMR) using market interconnectedness and volatilities. We study the relationship between our EMR and the VIX over the last two decades. The EMR is shown to be a novel approach to measuring global market risk, and an alternative to the VIX. Using data of 20 major stock markets, including G10 economies, we find spikes in our EMR index during the dotcom bubble, the global financial crisis, the European sovereign debt crisis, and the novel coronavirus pandemic. The result shows that the global financial crisis and the COVID-19 induced crisis record the historic highest spikes in financial market risk, suggesting stronger evidence of contagion in both periods.

Model of Risk Forewarn and Investment Decision in Stock Markets and Its Realization

Based on the discussion of characteristic and mechanism of the stock prices volatility in Chinese emerging stock markets, this research designs an index system for risk forewarn, and builds up an investment decision model based on the forewarn of the market risk signal. Then, on probing into the structure and function of the realization of the model, the paper presents the method of data interface.

Study of the Discount on Private Placements and Risk of Stock Market Crash in Listed Companies

With the gradual completion of the split-share structure reform,private placement has gradually become the mainstream of refinancing. One of the points that the practical and theoretical circles are widely concerned about is that the private placement price is often higher than the market price at the time of the private placement. High discounts are often accompanied by the transmission of benefits,and the increase in insider information will lead to the risk of a stock market crash? This paper intends to use the data of A-share listed companies from 2006 to 2015 to empirically study the relationship between the discount on private placements and the risk of stock market crash. At the same time,this paper examines whether the degree of information asymmetry plays a regulatory role in the relationship between the discount on private placements and the risk of stock market crash. This paper provides a certain reference for the regulatory authorities to improve the relevant laws and regulations in the private placement,and to provide a certain reference for the protection of the interests of small and medium-sized investors.

Multi scale risk measurement in electricity market:a wavelet based value at risk approach

Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is proposed. Empirical studies conduct in five Australian electricity markets, which evaluate the performances of both the proposed approach and the traditional ARMA-GARCH approach using the Kupiec backtesting procedure. Experimental results suggest that the proposed approach measures electricity market risks at higher accuracy and reliability than the bench mark ARMA-GARCH approach, as indicated by the higher p values during the Kupiec backtesting procedure. In addition, the new approach also provides more insight into the risk evolution process over time and helps in adjusting VaR estimates to the time horizons that best suit investor interests. The distribution of risk according to investor preferences is shown by decomposing VaR across different time horizons. This also provides important information for the appropriate aggregation of risk measures based on investor investment preferences.

Thoughts on Living Difficulties of Farmers and Marketing Economy in the Risk Society

The paper combs the problems about living difficulties of farmers and marketing economy in the risk society and puts forward another point of view that with the theory of risk society,reconsider the dilemma of living choices of farmers under the background of marketing economy.On the basis of the statistics,the paper discloses the trend of larger and larger disparities of incomes between urban and rural areas;the paper explains the risks and uncertainties of life choices with the background of deepening marketing economy.In order to understand the life dilemma of farmers and marketing economy in the risk society,the paper makes an analysis from perspectives of the relationships between risk society and markets,the risks of farmers' living choices.The results show that in the risk society,because of the division space from time,the personal farmers are devoid of the safe environment.Then the situation deepens to worse.In addition to the organization which is not in charge results in a situation that the personal farmers would take all risks by themselves.

Risk in A Concentrated Export Market

The export destination of China’s home textile products are considered to be highly concentrated. This is reflected by the statistical data of the past couple of years when, the top export destination of the following products-bedding products, curtain and towel- is United States.

极端天气场景下基于天气衍生品的电价风险管理

极端天气会导致线路跳闸,发电能力损失,负荷激增。市场环境下用户将承受高昂电价冲击,危及社会稳定。此时抑制电价飙升,管理电价风险十分重要。为此,设计了一种基于电价和发电损失容量的电力天气衍生品,可有效管理电价风险。首先,依据风险分解结构原理从源网荷及发电商报价角度分析了极端天气对电价的影响。其次,设计了考虑电价、天气为执行条件和基于损失容量与电价为收益函数的天气衍生品,并从理论层面分析了其效果。最后,结合预期效用最大化目标和电力市场出清模型进行发电商决策与电价模拟,使用条件风险价值(CVaR)指标评估了电价风险及衍生品效果。结果显示,所提电力天气衍生品使极端天气对发电商收入的冲击降低80%以上,用户电价均值降低约0.2%,用户电价风险降低20%以上,说明可有效控制电价风险,助力电力市场建设以及新型电力系统构建。

基于条件风险价值的虚拟电厂参与能量及备用市场的双层随机优化

为充分发挥虚拟电厂的灵活性价值,提出了虚拟电厂参与电能量及备用辅助服务市场的双层随机优化模型。上层基于条件风险价值理论建立了虚拟电厂参与电能量及备用辅助服务市场的两阶段风险决策模型,其中,第一阶段考虑新能源不确定性的潜在风险,建立了虚拟电厂参与能量和备用辅助服务市场的投标报价模型,第二阶段针对不同场景下的新能源出力建立了以虚拟电厂期望运行成本最小为目标的分布式资源优化调度模型;下层在已知各市场主体的投标报价信息后,开展电能量市场及备用辅助服务市场的联合出清。仿真分析表明,所提方法能够有效指导虚拟电厂规避新能源不确定性的潜在风险,并通过将备用价格提高到下一个边际机组的报价从而增加自身利润。